Covid 19 Analysis using Python

Importing modules

Task 1

from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
init_notebook_mode(connected=False)
import pandas as pd
import numpy as np
import plotly.express as px
import matplotlib.pyplot as plt 
print('modules are imported')

modules are imported

Task 1.1:

Loading the Dataset

dataset_url = 'https://raw.githubusercontent.com/datasets/covid-19/main/data/countries-aggregated.csv'
fname = 'data/countries-aggregated.csv'
df = pd.read_csv(fname)

df_31May21 = df[df.Date == '2020-05-31']

df_31May21.head()

	Date	Country	Confirmed	Recovered	Deaths
130	2020-05-31	Afghanistan	15208	1328	258
658	2020-05-31	Albania	1137	872	33
1186	2020-05-31	Algeria	9394	5748	653
1714	2020-05-31	Andorra	764	694	51
2242	2020-05-31	Angola	86	18	4

Task 1.2:

let's check the dataframe

df_31May21.head()

	Date	Country	Confirmed	Recovered	Deaths
130	2020-05-31	Afghanistan	15208	1328	258
658	2020-05-31	Albania	1137	872	33
1186	2020-05-31	Algeria	9394	5748	653
1714	2020-05-31	Andorra	764	694	51
2242	2020-05-31	Angola	86	18	4

df_31May21.tail()

	Date	Country	Confirmed	Recovered	Deaths
100450	2020-05-31	Vietnam	328	279	0
100978	2020-05-31	West Bank and Gaza	448	372	3
101506	2020-05-31	Yemen	323	14	80
102034	2020-05-31	Zambia	1057	779	7
102562	2020-05-31	Zimbabwe	178	29	4

let's check the shape of the dataframe

df_31May21.shape

(195, 5)

df.shape

(102960, 5)

Task 2.1 :

let's do some preprocessing

dfconf=df[df.Confirmed>0]

dfconf.head()

	Date	Country	Confirmed	Recovered	Deaths
33	2020-02-24	Afghanistan	1	0	0
34	2020-02-25	Afghanistan	1	0	0
35	2020-02-26	Afghanistan	1	0	0
36	2020-02-27	Afghanistan	1	0	0
37	2020-02-28	Afghanistan	1	0	0

dfconf.shape

(91970, 5)

let's see data related to a country for example Italy

dfconf[dfconf.Country=='Italy'].head(10)

	Date	Country	Confirmed	Recovered	Deaths
44889	2020-01-31	Italy	2	0	0
44890	2020-02-01	Italy	2	0	0
44891	2020-02-02	Italy	2	0	0
44892	2020-02-03	Italy	2	0	0
44893	2020-02-04	Italy	2	0	0
44894	2020-02-05	Italy	2	0	0
44895	2020-02-06	Italy	2	0	0
44896	2020-02-07	Italy	3	0	0
44897	2020-02-08	Italy	3	0	0
44898	2020-02-09	Italy	3	0	0

let's see Global spread of Covid19

fig = px.choropleth(dfconf, locations='Country', locationmode='country names', color='Confirmed', animation_frame='Date')
fig.layout.updatemenus[0].buttons[0].args[1]['frame']['duration'] = 30
fig.layout.updatemenus[0].buttons[0].args[1]['transition']['duration'] = 5
fig.update_geos(projection_type="equirectangular", visible=True, resolution=50)
fig.update_layout(
    title_text = 'Global Spread of Coronavirus',
    title_x = 0.5,
    geo=dict(
        showframe = False,
        showcoastlines = False,
    ))
#fig.show()
iplot(fig,show_link=False)